Journal of South China University of Technology(Natural Science Edition) ›› 2025, Vol. 53 ›› Issue (6): 104-118.doi: 10.12141/j.issn.1000-565X.240119

• Intelligent Transportation System • Previous Articles     Next Articles

A Review of The Multi-Level Urban Impacts of Shared Autonomous Vehicles

ZHONG Shaopeng1,2   LIU Ao1   ZHAI Junnuo1  FAN Meihan3  LI Xiyao4   LIN Yuan5   LI Zhenhua6   

  1. 1. Department of Transportation & Logisctics, Dalian University of Technology, Dalian 116024, Liaoning, China;

    2. International Urbanology Research Center, Center for Urban Governance of Zhejiang, Hangzhou 311121, Zhejiang, China;

    3. School of Information and Business Management, Dalian Neusoft University of Information, Dalian 116023, Liaoning, China;

    4. Engineering and Technology, Research Institute of Highway Ministry of Transport, Beijing 100088, China;

    5. School of Public Administration and Policy, Dalian University of Technology, Dalian 116024, Liaoning, China;

    6. State Key Lab of Intelligent Transportation System, Research Institute of Highway Ministry of Transport, Beijing 100088, China

  • Online:2025-06-25 Published:2024-12-06

Abstract: To gain a deeper understanding of the potential impacts of Shared Autonomous Vehicles (SAVs) on urban and promote the sustainable development of urban transportation systems, a comprehensive review and systematic analysis of the multi-level impacts of SAVs was conducted. The aim was to summarize the main contributions and shortcomings of previous studies and propose possible directions for future research. The review findings indicate that existing studies primarily focus on the short-term impacts of SAVs on the transportation system, including residents' travel behavior and road traffic flow. However, there is relatively little research on the long-term impacts of SAVs, particularly concerning urban accessibility, environment, and energy. While some studies have revealed potential negative effects of SAVs, such as adverse impacts on the environment or accessibility, few have proposed targeted and effective development strategies. Additionally, in terms of methods, existing studies mainly rely on qualitative analysis or independent transportation demand models for projections and simulations, which have certain limitations regarding the reliability of the results. Future research should develop the integrated land use and transportation model and combine the integrated model with data-driven methods to more accurately, comprehensively, and systematically analyze the long-term (negative) impacts of SAV introduction on urban land use, environment, and energy. This approach should also aim to propose targeted development strategies and countermeasures to optimize the application of SAVs, minimize their potential negative impacts, and promote the development of urban transportation systems towards efficiency, intelligence, and sustainability.

Key words: intelligent transportation, sharing autonomous vehicle, land use and transportation, urban impact, accessibility